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Modelling of the Environmental Distribution and Fate of Persistent Organic Pollutants on a National, European and Global Scale (EPG 1/3/169).
Andy J. Sweetman, Konstantinos Prevedouros, Nick Farrar, Foday Jaward
and Kevin C. Jones
Department of Environmental Science, Institute of Environmental and Natural Sciences Lancaster University, Lancaster, LA1 4YQ, UK
Phone: 01524-593972 Fax: 01524-593985
Email: [email protected]
mailto:[email protected]
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Executive summary
The fate and behaviour of persistent organic pollutants (POPs) in the environment has
attracted considerable scientific and political interest, arising from concern over human
exposure to these chemicals and their discovery in pristine environments far from source
regions. The ability of certain POPs to undergo long range atmospheric transport (LRAT) has
resulted in the negotiation of protocols (e.g. UN/ECE, UNEP) for their reduction or
elimination, to reduce the risks to regional and global environments. A number of chemicals
are currently being investigated for inclusion on the UN/ECE POPs protocol list of priority
compounds. The development of such protocols recognises the regional and global nature of
many POP compounds. This implies that control of such chemicals requires multi-lateral
agreements. However, the control and reduction of primary sources of such compounds is
only part of the process as there may still be diffuse and secondary sources that need to be
identified and quantified. Therefore a complete source inventory and an understanding is
the multi-media fate and behaviour of individual POPs is essential if effective control is to
be achieved.
Lancaster University has developed a number of modelling tools that can be used to
investigate the potential environmental impact of existing and candidate POPs. The most
recent model development is a regionally segmented multimedia fate model covering the
European continent. This model has been designed to examine the environmental fate and
behaviour of a wide range of chemicals and to investigate a number of emission scenarios
and source reduction strategies. It can also be used as a predictive tool to identify
potentially important sinks and for estimating the potential for long-range atmospheric
transport. Models such as this can be helpful in understanding the movement from source to
sinks. They can incorporate secondary or diffusive sources to land or water as well as
directly to air. Whilst further refinement to model design and parameterisation is required,
these models are already being used to direct research by identifying important fate
processes and sinks that should receive further attention. In summary, fate models are
important tools for policy making; by helping to prioritise chemicals, highlight research
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priorities and ultimately provide quantitative links between sources, environmental levels
and exposure. Importantly, they can direct policy by identifying processes which may be
subject to control and by providing quantitative information regarding the effectiveness of
such control measures.
During the course of this contract scientific manuscripts have been prepared on a range of
aspects of the work which have been submitted to various journals. These papers have been
included in this report as they represent concise accounts of the work undertaken which
have also been peer reviewed (or in the process of review) by the scientific community.
The model development work is complimented by a number of measurement exercises aimed
at improving the description of key processes and providing datasets for calibration and
validation. Although validation of models such as these is challenging an international group
of experts has been formed coordinated by MSC-E in Moscow. Lancaster University is an
active member of this group which is currently developing a framework which can be used to
compare a number of POP fate models and to eventually provide meaningful validation with
measurement data.
Physicochemical database and candidate POP compounds
A web based physicochemical and environmental fate database has been prepared for a wide
range of POPs and related compounds. The database and the results of a range of screening
model runs are available on the Lancaster University Environmental Science Department
server (www.es.lancs.ac.uk/ecerg/kcjgroup/modelling.html). These databases contain a range
of physicochemical data that can be used to provide an indication of environmental
behaviour and to provide input to fate and behaviour models. The database is continually
updated as new data becomes available
An important task, therefore, is to identify candidate POPs based on a knowledge of their
physicochemical properties and their production and use patterns. To aid this process
Lancaster hosts (on behalf of Defra) a web based physicochemical and environmental fate
database for a wide range of POPs and related compounds. An equally important task is to
http://www.es.lancs.ac.uk/ecerg/kcjgroup/modelling.html
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continually update the emission inventory associated with these compounds. In some cases,
this requires undertaking preliminary estimates as full inventories are not yet available. The
current list of candidate POPs under discussion include the following:
Endosulfan, Hexachlorobutadiene, Pentachlorobenzene, Dicofol, Polychlorinated naphthalenes, Pentachlorophenol, Short-chain Chlorinated Paraffins and Pentabromodiphenylether. Seasonal and long-term trends in atmospheric PAH concentrations: evidence and implications The objective of this study was to examine seasonal and temporal trends of atmospheric
PAHs, to shed light on the factors which exert a dominant influence over ambient levels.
Urban centres in the UK have concentrations 1-2 orders of magnitude higher than in rural
Europe and up to 3 orders of magnitude higher than Arctic Canada. Atmospheric monitoring
data for selected polynuclear aromatic hydrocarbons (PAHs) have been compiled from
remote, rural and urban locations in the UK, Sweden, Finland and Arctic Canada.
Interpretation of the data suggests that proximity to primary sources drives PAH air
concentrations. Seasonality, with winter (W) > summer (S), was apparent for most
compounds at most sites; high molecular weight compounds (e.g. benzo[a]pyrene) showed
this most clearly and consistently. Some low molecular weight compounds (e.g. phenanthrene)
sometimes displayed S>W seasonality at some rural locations. Strong W>S seasonality is
linked to seasonally-dependent sources which are greater in winter. This implicates
inefficient combustion processes, notably the diffusive domestic burning of wood and coal.
However, sometimes seasonality can also be strongly influenced by broad changes in
meteorology and air mass origin (e.g. in the Canadian Arctic). The datasets examined here
suggest a downward trend for many PAHs at some sites, but this is not apparent for all
sites and compounds. The inherent noise in ambient air monitoring data makes it difficult to
derive unambiguous evidence of underlying declines, to confirm the effectiveness of
international source reduction measures.
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Modelling the atmospheric fate and seasonality of polycyclic aromatic hydrocarbons in the UK This study into atmospheric fate and behaviour modelling of PAHs had three main
objectives: 1). to investigate the balance between estimated national atmospheric emissions
of 6 selected PAHs and observed ambient measurements for the UK, as a means of testing
the current emission estimates; 2). to investigate the potential influence of seasonally
dependent environmental fate processes on the observed seasonality of air concentrations;
and 3). after undertaking the first two objectives, to make inferences about the likely
magnitude of seasonal differences in sources. When addressing objective 1 with annually
averaged emissions data, it appeared that the UK PAH atmospheric emissions inventory was
reasonably reliable for fluorene, fluoranthene, pyrene, benzo[a]pyrene and
benzo[ghi]perylene but not so for phenanthrene. However, more detailed analysis of the
seasonality in environmental processes which may influence ambient levels, showed that the
directions and/or magnitudes of the predicted seasonality did not coincide with field
observations. This indicates either that our understanding of the environmental fate and
behaviour of PAHs is still limited, and/or that there are uncertainties in the emissions
inventories. It is suggested that better quantification of PAH sources is needed. For 3- and
4-ringed compounds, this should focus on those sources which increase with temperature,
such as volatilisation from soil, water, vegetation and urban surfaces, and possible
microbially-mediated formation mechanisms. The study also suggests that the contributions
of inefficient, diffusive combustion processes (e.g. domestic coal/wood burning) may be
underestimated as a source of the toxicologically significant higher molecular weight
species in the winter. It was concluded that many signatory countries to the UNECE POPs
protocol (which requires them to reduce national PAH emissions to 1990 levels) will
experience difficulties in demonstrating compliance, because source inventories for 1990
and contemporary situations are clearly subject to major uncertainties.
Modelling the fate of persistent organic pollutants in Europe: parameterisation of a gridded distribution model A regionally segmented multimedia fate model for the European continent has been
developed to provide fate and behaviour information for POP compounds on a continental
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scale. A manuscript has been prepared which describes the model construction and
parameterisation together with an illustrative steady-state case study examining the fate
of γ-HCH (lindane) based on 1998 emission data. The study builds on the regionally
segmented BETR North America model structure and describes the regional segmentation
and parameterisation for Europe. The European continent is described by a 5° x 5° grid,
leading to 50 regions together with 4 perimetric boxes representing regions buffering the
European environment. Each zone comprises seven compartments including; upper and lower
atmosphere, soil, vegetation, fresh water and sediment and coastal water. Inter-regions
flows of air and water are described, exploiting information originating from GIS databases
and other georeferenced data. The model is primarily designed to describe the fate of
Persistent Organic Pollutants (POPs) within the European environment by examining chemical
partitioning and degradation in each region, and inter-region transport either under steady-
state conditions or fully dynamically. A test case scenario is presented which examines the
fate of estimated spatially resolved atmospheric emissions of lindane throughout Europe
within the lower atmosphere and surface soil compartments. In accordance with the
predominant wind direction in Europe, the model predicts high concentrations close to the
major sources as well as towards Central and Northeast regions. Elevated soil
concentrations in Scandinavian soils provide further evidence of the potential of increased
scavenging by forests and subsequent accumulation by organic-rich terrestrial surfaces.
Initial model predictions have revealed a factor of 5-10 underestimation of lindane
concentrations in the atmosphere. This is explained by an underestimation of source
strength and/or an underestimation of European background levels. The model presented
can further be used to predict deposition fluxes and chemical inventories, and it can also be
adapted to provide characteristic travel distances and overall environmental persistence,
which can be compared to other long-range transport prediction methods.
Spatial mapping of POP chemicals using passive air samplers During the summer of 2002 an ambient air passive sampling campaign for a range of
persistent organic pollutants was carried out at the continental scale. This was achieved
using a sampling system consisting of polyurethane foam disks, which were: prepared at
Lancaster University; sealed to prevent contamination; sent out by courier to volunteers
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participating in different countries; exposed for 6 weeks; collected; re-sealed and returned
to the laboratory for analysis. The study area covered most of Europe, a region with a
history of extensive POPs usage and emission, and with marked national differences in
population density, the degree of urbanisation and industrial/agricultural development.
The results have been split into two manuscripts covering different compounds
groups/classes. Samplers were deployed at remote/rural/urban locations in 22 countries and
analysed for PCBs, a range of organochlorine pesticides (HCB, HCHs, DDT, DDE), PBDEs,
PAHs and PCNs. Calculated air concentrations were in line with those obtained by
conventional active air sampling techniques. The geographical pattern of all compounds
reflected suspected regional emission patterns and highlighted localised hotspots. PCB and
PBDE levels varied by over 2 orders of magnitude; highest values were detected in areas of
high usage and were linked to urbanised areas. HCB was relatively uniformly distributed,
reflecting its persistence and high degree of mixing in air. Higher γ-HCH, DDT and DDE
levels generally occurred in S and E Europe. Calculated air concentrations for PAHs and
PCNs were also in line with those obtained by conventional active air sampling techniques.
The geographical compound distribution reflected suspected regional emission patterns and
highlighted localised hotspots. PAH and PCN levels varied by over 2 orders of magnitude;
the implications for sources are discussed.
A further experimental passive air sampler was also sent out to selected participants during
the European campaign which was designed to react more rapidly to changing ambient air
concentrations of POP compounds. The use of polymer coated glass (POG) samplers for
environmental sampling has been proposed and developed by Dr Frank Gobas (Simon Fraser
University, British Columbia, Ca) and Dr Tom Harner (MSC, Toronto, Ca). Initially these
devices were used to sample water and biota but have recently been adapted to measure
POPs in ambient air. For the purposes of this study the POG was housed in a sampling
chamber to allow deployment in a sheltered and controlled environment. The POG air
sampler, composed of a rapidly equilibrating polymeric stationary phase (Harner et al.
2003), was deployed at 41 sites across 20 countries. Based on an estimated uptake rate of ~
3m3 per day, samplers were theoretically exposed to approximately 21 m3 of air. However,
for some of the lighter compounds (i.e. high vapour pressure) equilibrium was achieved. In
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order to convert the amount of chemical recovered from the EVA a partition coefficient
between EVA and air is required. These partition coefficients can be related to the octanol-
air partition coefficient which in turn can be corrected for temperature as required.
Study into the factors controlling the uptake of POP chemicals by passive air samplers using controlled laboratory chambers As previously mentioned, a number of passive sampler devices have been utilised to sample
POP chemicals in the atmosphere including polyurethane foam, polymer coated glass,
polyethylene and soil. However, in order to provide quantitative data that can be compared
with concentration data measured by other techniques such as Hi-volume samplers, the
uptake kinetics of the samplers needs to understood. As a result a laboratory study has
been carried out to identify the key parameters controlling the exchange of chemicals
between the atmosphere and the sampling device. For the purposes of this study SPMDs
(semi-permeable membrane devices) were chosen although the sampling processes and
mechanisms are broadly similar across all sampler types and hence the findings of this study
are applicable elsewhere. The results suggested that both wind speed and temperature
exert a effect on the depuration of phenanthrene from SPMDs. The effect of varying the
wind speed across the SPMD controls the thickness of the boundary layer and hence the
distance through which the phenanthrene has to diffuse. However, this effect appears to
be limited to lower wind speeds above which the effect on the boundary layer is minimal.
The effect of increasing the depuration rate by increasing temperature could also be
related to diffusion through the boundary layer. As the temperature increases so does the
molecular diffusion rate although this effect is limited a 20ºC increase in temperature
results in a 13% increase in molecular diffusion. Temperature is also likely to control the
diffusion rates in the triolein and through the polyethylene which would require further
investigation.
POP multimedia model inter-comparison study (MSC-E, Moscow) Multi-media POP fate and behaviour models are now widely available and are slowly being
incorporated into risk assessment procedures. However, in order to improve accuracy and
obtain comparable results the harmonization of model output is required. The
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intercomparison of different types of POP transport models has been included in the
recommendations of the WMO/UNEP/EMEP Workshop on modelling of atmospheric
transport and deposition of POP and HM, Geneva, November 1999. Later on, the work of
intercomparison of POP long-range transport models was included to the EMEP work-
programme. The recent OECD/UNEP Workshop on the use of multimedia models for
estimating overall persistence and long-range transport, Ottawa, October 2001 also marked
a necessity of intercomparison study of POP multimedia models of different complexity.
MSC-E, Moscow, has initiated an intercomparison exercise that will take place over the next
few years that hopes to achieve improved model harmonization.
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Modelling of the Environmental Distribution and Fate of Persistent Organic Pollutants on
a National, European and Global Scale (EPG 1/3/169).
Authors: Andy J. Sweetman, Costas Prevedouros, Nick Farrar, Foday Jaward and
Kevin C. Jones
Prepared for Defra, AEQ Division Project Manager: Alan Irving Contents Page Section Executive summary 1 1 Introduction 11 2 Physicochemical database and candidate POP compounds 14 3 Seasonal and long-term trends in atmospheric PAH 23
concentrations: evidence and implications 4 Modelling the atmospheric fate and seasonality of polycyclic 46
aromatic hydrocarbons in the UK 5 Modelling the fate of persistent organic pollutants in Europe: 74
parameterisation of a gridded distribution model 6 Passive air sampling of PCBs, PBDEs and organochlorine pesticides 99
across Europe 7 Passive air sampling of PAHs and PCNs across Europe 124 8 Passive sampling across Europe campaign using short term 150
air sampling using polymer coated glass samplers (POG) 9 Study into the factors controlling the uptake of POP chemicals 160
by passive air samplers using controlled laboratory chambers 10 POP multimedia model inter-comparison study (MSC-E, Moscow) 167
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Section 1 Introduction The fate and behaviour of persistent organic pollutants (POPs) in the environment has attracted considerable scientific and political interest, arising from concern over human exposure to these chemicals and their discovery in pristine environments far from source regions. The ability of certain POPs to undergo long range atmospheric transport (LRAT) has resulted in the negotiation of protocols (e.g. UN/ECE, UNEP) for their reduction or elimination, to reduce the risks to regional and global environments. A number of chemicals are currently being investigated for inclusion on the UN/ECE POPs protocol list of priority compounds. Synthetic organic chemicals are released into the environment through a range of processes which include; release during the production process, release during use (e.g. pesticides), or accidental release during combustion processes (e.g. dioxins). Once in the environment, some of these chemicals have been shown to exhibit detrimental effects on wildlife and some have been shown to bioaccumulate through food chains resulting in high concentrations in top predators e.g. man. If we are to achieve the sustainable use of chemicals then we need a validated process of risk assessment through which we can evaluate the impact of both existing chemicals and those which will be produced in the future. The process of risk assessment currently uses a combination of predictive models, and worst case scenarios, to calculate environmental concentrations based on a knowledge of chemical production/use and release and information on their likely behaviour in the environment. These can be compared to environmental quality standards (EQSs) which provide quantitative information on tolerable levels at which no harm to the environment (or man) is likely. In particular, the ability to link atmospheric concentrations to concentrations in other media, including accumulation through foodchains, is vital for our successful management of chemicals in the environment. The development of reliable and validated models is essential to ensure that the risk assessment process is effective and transparent to the regulated and the regulator. We currently have a suite of models and approaches which can be used and adapted to investigate these issues. These include a UK scale dynamic multi-media model, a European gridded steady state/dynamic model and an atmospheric fate and behaviour model which can be used to investigate seasonality in emissions and removal processes. The European model is currently being used to participate in an international model intercomparison exercise. All of the models developed at Lancaster are undergoing a process of validation and further improvement as part of a new Defra contract entitled Research into the further development of regional and national modelling of persistent organic pollutants, and review of the UN/ECE POPs protocol EPG 1/3/203. The following table outlines a number of objectives and milestones that were identified at the beginning of this contract which are briefly discussed below.
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The following milestones were set out in the project proposal.
Task Details
1 Compilation of database to identify candidate POPs 2 Compilation of physicochemical database for 50 candidate POPs 3 Place database on website 4 Improvements to UK model 5 Construct European regional model 6 Adapt/improve global model where applicable. 7 Design and construct passive sampler deployment device 8 Deploy passive samplers across EUROPE 9 Air-surface exchange process study 10 UK temporal trends study 11 Investigate human model adaptation and incproporation
• The first three tasks involving the compilation of the physicochemical database,
preliminary screening and web publishing were successfully completed. The database can be found at http://www.es.lancs.ac.uk/ecerg/kcjgroup/modelling.html and will be constantly updated and improved during the current contract with Defra.
• Task 4 was also completed with final improvements to the UK model which resulted in a
manuscript being published in Environmental Toxicology and Chemistry. Sweetman, A.J., Cousins, I.T., Seth, R., Jones, K.C. and Mackay, D. (2002) A dynamic Level IV multimedia environmental model: Application to the fate of PCBs in the United Kingdom over a 40-year period. Environmental Toxicology and Chemistry, 21(5), 930-940. The model has been further developed and modified to examine the seasonality of PAH emissions and their fate in the UK atmosphere. Details of these studies can be found in sections 3 and 4 of this report.
• Task 5 involved the re-parameterisation of the BeTr North American model developed
at Trent University, Canada, for Europe with the collaborative assistance of Professor Donald Mackay. This project has recently been completed and a manuscript prepared with γ-HCH as the test chemical. Details of the model can be found in section 5 and the manuscript will be published in Environmental Pollution later in 2003.
• Task 6 has involved collaborative research with other groups that are examining the
global fate of POP chemicals. These include: Prof. Don Mackay, Trent University, Canada Dr. Matt MacLeod, Lawrence Berkeley National Laboratory, USA Dr. Gerhard Lammel, Max Planck Inst., Germany Dr. Martin Scheringer, ETH, Switzerland
This work is still on-going and will be reported under the new Defra contract.
http://www.es.lancs.ac.uk/ecerg/kcjgroup/modelling.html
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• Task 7 and 8 have involved a European scale passive sampling campaign carried out during the summer of 2002. The analytical data has recently been completed. Two types of sampler were deployed across a number of widely dispersed sites and analysed for a range of POP chemicals. Details of the study are contained in sections 6, 7 and 8 of this report and are currently going through the peer review process for publication in the open literature. A further passive sampling study is being carried out under the current Defra contract which aims to quantify the spatial distribution of short-chain chlorinated paraffins in the UK atmosphere.
• Task 9 has been addressed in the development of the European model as the air-
surface exchange of POP chemicals is a key part of transport description and an important factor in determining overall fate. However, this is an extremely important area of POPs research and a number of studies (both laboratory and modelling) are currently on-going which will be reported under the new contract.
• Task 10 was designed to use a range of methodologies, including modelling, to
investigate temporal trends of POP chemicals in the UK environment. The UK atmospheric PAH study investigated the long-term trend data that is being provided by the TOMPs network and compared it to datasets from other countries. A further study using a range of modelling techniques has investigated the long-term trends of PBDEs in the UK and North American environments. In particular, this work focussed on sources of these compounds to the atmosphere. Details can be found in: Alcock, R.E., Sweetman, A.J., Prevedouros, K. and Jones, K.C. (2003) Understanding levels and trends of BDE-47 in the UK and North America: an assessment of principal reservoirs and source inputs. Environment International, 29(6), 691-698
• The objective of Task 11 was to explore linking human exposure models to fate and
exposure models such as the European model developed under this contract. The Lancaster group have been involved with developing terrestrial food chain transfer algorithms for POP chemicals with the aim of predicting human exposure. Currently this area of research is limited to local exposure resulting from point sourece emissions. The Environment Agency commissioned Lancaster University to develop a model framework to investigate the release of PCDD/Fs and PCBs from sources such as municipal waste incinerators (MWIs) and to quanitify the potential impact on human exposure at a local scale. Predicted environmental and foodstuff concentratations are then combined with dietary information and the intake predictions compared to the current TDI and UK typical ingestion rates provided by the Food Standards Agency. Whilst this model currently works on a local scale, the food chain transfer algorithms are applicable to larger scale models. A potential end point of regional scale models will be to incorporate such algorithms and provide an estimate of human exposure resulting from a particular emission scenario. However, further information would be required before this could be accomplished, such as the incorporation of regional differences in diet etc. This area is being investigated under the current contract with Defra.
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Section 2 Physicochemical database and candidate POP compounds
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Introduction Persistent organic pollutants have been the subject of internationally agreed protocols to ensure that their impact on humans and the environment are minimized. Under the UNECE Convention there are twelve POPs (or chemical groups) which have been targeted for elimination or reduction. They have been selected because of concerns over their persistence in the environment, their ability to undergo long range transport and their ability to bioaccumulate through food chains. As a result of these properties and their potential to exert toxic effects, efforts are being made to reduce environmental and human exposure. However, there are many chemicals being produced that may have similar properties and hence may be considered POPs. An important task, therefore, is to identify candidate POPs based on a knowledge of their physicochemical properties and their production and use patterns. Compilation of database to identify candidate POPs A web based physicochemical and environmental fate database has been prepared for a wide range of POPs and related compounds. The database and the results of a range of screening model runs are available on the Lancaster University Environmental Science Department server (www.es.lancs.ac.uk/ecerg/kcjgroup/modelling.html) with the current front page shown in Figure 1. Figure 1 - Web page
http://www.es.lancs.ac.uk/ecerg/kcjgroup/modelling.html
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These databases contain a range of physicochemical data that can be used to provide an indication of environmental behaviour and to provide input to fate and behaviour models. Data includes: F Fugacity ratio. The fugacity ratio represents the ratio of solid to liquid solubility or vapour pressure. F is calculated from MP and is unity for liquids. LeBas (cm3 mol-l). Theoretical calculation of molar volume. Useful for developing quantitative structure activity relationships (QSPRs). Aq.sol. (g m-3). Aqueous solubility. Owing to the hydrophobic nature of many POPs their solubility in water is low, generally less than 1 mg l-1. This makes measurement methods difficult and hence data is only available for selected congeners. However, both aqueous solubility and Kow are determined by the activity of contaminants in water which results in a strong correlation between these properties. When not reported a linear correlation between the sub-cooled liquid vapour pressure and Kow can be used to predict this property.
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The solid vapour pressure is an important property for POPs as it describes their 'solubility' in air which partly determines their exchange with surfaces such as soil and water, but also their partitioning onto atmospheric particles. These processes will be responsible for determining their ability to undergo long range transport. Measurement techniques such as gas saturation are difficult and have only been carried out for a range of contaminants. For many POPs, vapour pressures are low ranging from 1 to 10-5 Pa which classifies them as semi-volatile. Octanol-water partition coefficient - Kow (dimensionless). The octanol-water partition coefficient describes the equilibrium partitioning behaviour of a chemical between water and the lipid substitute octanol. POPs are hydrophobic in nature with Kow expressed on a log10 scale ranging from 3.6 for endosulphan to 8 for octachlorodibenzo-p-dioxin. Generally, values for Kow are determined experimentally but estimation methods structural properties can be employed. Much of the data in Table A 1 are taken from Mackay (2000). However, in order to provide values for some contaminants, particular for congeners within a contaminant group, we have used a quantitative structure property relationship (QSPR) which uses molecular volume (LeBas method) as the molecular descriptor. H Henry's law constant (Pa mol. m-3). The Henry's law constant describes the equilibrium partitioning behaviour of a chemical between water and air phases and hence is an important descriptor of atmospheric-surface exchange. The data in Table A 1 has been calculated using the ratio between the sub-cooled liquid vapour pressure and sub-cooled liquid aqueous solubility. H' Dimensionless Henry's Law Constant (calculated as H/RT) Koa Octanol-air partition coefficient (dimensionless ). The octanol-air partition coefficient describes the equilibrium partitioning behaviour of a chemical between air and the lipid substitute octanol. It has been shown to be a useful descriptor of atmospheric vapour-particle partitioning and surface-air exchange. Reaction rate. Reaction or degradation rates are virtually impossible to assign single values as they vary not only with the intrinsic properties of the chemical but on the nature of the surrounding environment. Factors such as sunlight intensity, hydroxyl radical concentration and the nature of the microbial community, as well as temperature, affect a chemicals half life so it is impossible to a assign single reliable half-life. In the absence of measured atmospheric reaction rate data for individual congeners Mackay et al. (2000) have provided a semi-quantitative estimation of persistence in a range of environmental media. Mackay, D., Shui, w- Y. and Ma, K-C.(2000) Illustrated handbook ofphysical-chemical properties and environmental fate for organic chemicals. Lewis Publ. A number of compounds and compound groups are currently being considered as candidate POP compounds for possible inclusion on the UNECE protocol list. These inlclude: 1. Endosulfan: proposed by Germany
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Organochlorine insecticide used for plant protection - primarily cotton, tobacco, tea also used in wood preservatives etc. Currently European total use is approximately 500 tonnes with highest usage in Southern Europe. Usage in the UK has declined according to Pesticide Survey Group from 1,660 kg in 2000 to 119 kg in 2001 - the main continuing use is on blackcurrants. Two isomers (alpha and beta), from which the α- isomer is considered to be more volatile. Large particle-bound fraction. Short atmospheric half-life (1-3 days), low Log Kow (
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Structurally similar to the PCBs. Hydrophobic, stable and good insulators. Uses include cable insulation, wood preservation and in capacitors. Used to be a HPV chemical. Production in the UK stopped by the end of the 1960s. Potential for LRT, bioaccumulation, although not enough information on persistence/degradation in various environmental media. Air concentrations have been measured as part of the HAPs program, with mean ΣPCN levels of 111 pg m-3 and 85 pg m-3 for Hazelrigg and Chilton, respectively. Totals are generally dominated by the tetra-chlorinated congeners. 6. Pentachlorophenol: proposed by Poland (draft) PCP is a biocide which may contain other chlorophenols and PCDD/Fs as impurities. Major use is as a wood treatment. EU countries stopped producing PCP in 1992 but significant amounts have been imported until the end of the 1990s. The UK was one of the main importers: 30 tonnes in 1996 and 15 tonnes in 1999, mostly to manufacture sodium pentachlorophenyl laurate (PCPL). PCPL is used in the preservation of textiles, which are subject to degradation by fungi and bacteria (for heavy duty military transport and tent textiles). PCP has a low bioaccumulation potential, but is mobile and relatively persistent. The aquatic environment is most sensitive to PCP. Measured PCP concentrations in freshwater have been as high as 0.2 µg l-1 (1995) in the UK. Not much data available for the UK. Further inventory work is required to establish how much is currently in the environment (i.e. in treated wood) and the potential for on-going sources. 7. Short-chain Chlorinated Paraffins: proposed by Canada (draft) The main uses of SCCPs are in metal working fluids, as plasticisers in paints, coatings and sealants, as flame retardant in rubbers and textiles, and in leather processing. Emissions can occur either during production or during their use in metalworking processes. OSPAR have reported that use of SCCPs in Europe has decreased from 13,000 tonnes in 1994 to 4,000 tonnes in 1998. Historical and current use in the UK is unknown the UK is also a major exporter. SCCPs exhibit low vapour pressures, very low water solubilities and Log Kows ~6-7, and hence there is potential for bioaccumulation. They also exhibit short half-lives in air (~1-3 d) and decreasing vapour pressure with increasing in carbon chain length. We are currently planning a spatial mapping sampling campaign using passive air samplers. Levels in the UK atmosphere measured at Hazelrigg ranged from 5 to 1090 pg m-3 with a median value of 225 pg m-3. 8. Pentabromodiphenylether: proposed by Finland/Sweden. We have recently completed a manuscript which attempts to quantify historical production and use of pentabromodiphenylethers particularly, BDE-47. It has been published in a special issue of Environment International and represents our current understanding of PBDE production and environmental fate and behaviour. The results present some interesting thoughts about possible routes of human exposure.
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Alcock, R.E., Sweetman, A.J., Prevedouros, K. and Jones, K.C. (2003) Understanding levels and trends of BDE-47 in the UK and North America: an assessment of principal reservoirs and source inputs. Environment International, 29(6), 691-698 Table 1 contains a summary of available physicochemical data for selected POP candidate compounds.
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Table 1 Summary physicochemical data for selected candidate POPs Chemical CAS No MW (g/mol) MP (oC) Vp (Pa) Sw (g/m3) Log Kow T1/2 air (h) T1/2 water (h) T1/2 soil (h) T1/2 sed (h)
α-endosulfan 959-98-8 406.95 109 0.0013 0.5 3.6 72 720 1200 1200
β-endosulfan 33213-65-9 406.95 213 0.006 0.3 3.8 72 720 1200 1200
Pentachlorobenzene 608-93-5 250.3 86 2.2 0.56 5 7200 7200 3600 3600
Pentachlorophenol 87-86-5 266.34 190 0.12 14 5.05 170 170 1700 550
Hexachlorobutadiene 87-68-3 260.7 -21 20 3.2 4.9 1700 550 550 550
Dicofol 115-32-2 370.5 0.0000016 5 72 72 720 1200
PCNs 162.5 - 404 -2- 200 5 - 10-5 3 - 8 10-5 3.9 - 8.3 24 - 10000 n/a n/a n/a
C12H20Cl6 377 41.4 2.10E-03 2.46E-03 6.89
C12H16Cl10 520 101.1 1.80E-06 1.90E-04 7.81
C16H31Cl3 331 41.7 6.78E-02 9.80E-04 7.14
C16H21Cl13 681 190.9 8.47E-09 9.00E-06 8.88
PeBDE (47) 485.5 80.5 8.18E-05 9.32E-03 6.67 256 3600 3600 14440
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Section 3 Manuscript title: Seasonal and long-term trends in atmospheric PAH concentrations: Evidence and implications Authors and affiliations: Konstantinos Prevedouros, Crispin J. Halsall, Kevin C. Jones, Robert G. M. Lee and Andrew J. Sweetman Environmental Science Department, Institute of Environmental and Natural Sciences, Lancaster University, Lancaster, LA1 4YQ, United Kingdom. Eva Brorström-Lundén IVL, Swedish Environmental Research Institute, Box 47086, SE-402 58 Göteborg, Sweden. Submission journal: Environmental Pollution . Elsevier Press. www.elsevier.com
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Abstract
Atmospheric monitoring data for selected polynuclear aromatic hydrocarbons (PAHs) were
compiled from remote, rural and urban locations in the UK, Sweden, Finland and Arctic
Canada. The objective was to examine the seasonal and temporal trends, to shed light on the
factors which exert a dominant influence over ambient PAH levels. Urban centres in the UK
have concentrations 1-2 orders of magnitude higher than in rural Europe and up to 3 orders
of magnitude higher than Arctic Canada. Interpretation of the data suggests that proximity
to primary sources drives PAH air concentrations. Seasonality, with winter (W) > summer
(S), was apparent for most compounds at most sites; high molecular weight compounds (e.g.
benzo[a]pyrene) showed this most clearly and consistently. Some low molecular weight
compounds (e.g. phenanthrene) sometimes displayed S>W seasonality at some rural locations.
Strong W>S seasonality is linked to seasonally-dependent sources which are greater in
winter. This implicates inefficient combustion processes, notably the diffusive domestic
burning of wood and coal. However, sometimes seasonality can also be strongly influenced by
broad changes in meteorology and air mass origin (e.g. in the Canadian Arctic). The datasets
examined here suggest a downward trend for many PAHs at some sites, but this is not
apparent for all sites and compounds. The inherent noise in ambient air monitoring data
makes it difficult to derive unambiguous evidence of underlying declines, to confirm the
effectiveness of international source reduction measures.
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Introduction
Polynuclear aromatic hydrocarbons (PAHs) are amongst the groups of compounds defined as
persistent organic pollutants (POPs) and subject to international atmospheric emissions
controls under the 1998 United Nations Economic Commission for Europe (UNECE) protocol
(1,2). PAHs are subject to long-range atmospheric transport (LRAT) and there are concerns
over the carcinogenicity of some PAH compounds (1-3). Signatories to the POPs protocol
undertake to reduce atmospheric emissions of PAHs to the levels of the reference year
1990. Some countries have adopted, or are considering, air quality standards for selected
PAHs; the United Kingdom has a proposed annually averaged standard for benzo[a]pyrene of
0.25 ng/m3, for example. This value can be exceeded in both urban and rural areas (4).
These regulatory developments raise interesting scientific issues: a) are the major PAH
sources and national emissions inventories well enough established, now and for the 1990
reference year, to ensure compliance with the POPs protocol?; b) what are the trends in
atmospheric concentrations of PAHs over the last decade or so?; c) how variable are PAH
concentrations seasonally and spatially?; and, d) what are the implications of this variability
for sources and compliance with an annually averaged air quality standard?
Despite several years of study, there is still considerable uncertainty over several aspects
of the atmospheric sources and behaviour of PAHs. For example, whilst some inventories
point towards domestic burning of coal and wood as the dominant source of PAHs to the
atmosphere, others implicate emissions from vehicles, or metal smelting/process operations
(2,5). Without reliable information on sources, it is difficult to conceive how a country can
accurately assess whether it is reducing emissions in line with its commitments to
international agreements.
One useful approach to help distinguish between the dominant source categories is to
examine ambient monitoring data. For example, if ambient air measurements display
seasonality, this would provide clues about the dominant sources; some sources are seasonal
(e.g. domestic heating; natural fire events), whilst others are not (e.g. industrial combustion,
aluminium and coke production, petroleum refining). However, air concentrations are
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controlled by a complex array of variables, as depicted in Figure 1. Some of these factors
may also influence the seasonality in ambient air measurements, notably secondary sources
of PAHs into the atmosphere (i.e. possible volatilisation from soil, water, vegetation or/and
urban surfaces); atmospheric loss/removal processes, such as wet deposition, reactions with
OH radicals, scavenging by vegetation; dilution/advection factors, influenced by wind speed
and direction and mixed boundary layer height. Finally, temperature changes drive the gas :
particle distribution and atmospheric reaction rates of PAHs.
In this paper, data from monitoring programmes were compiled and assessed, to evaluate
the underlying trends and seasonality of PAH air concentrations. Data were considered for
different compounds from a range of countries (UK, Sweden, Finland and Arctic Canada) and
environments (urban, rural, coastal, remote). These datasets were selected because they
provided time series over several years. They constitute some of the few consistent
sources of measurement data available internationally. Our objective was to examine the
spatial and temporal trends, to shed light on the factors which exert a dominant influence
over ambient PAH levels, and to briefly consider the implications for sources and regulation.
Initial remarks on seasonality in air concentrations
Studies have been performed which provide data on the seasonality of atmospheric PAHs.
Halsall et al. (6) reported data for 1991-1992 at 4 urban monitoring sites in the UK (London,
Manchester, Cardiff and Stevenage). They noted only a small seasonal variation for the
ΣPAH (vapour plus particulate) concentration and selected lighter compounds (e.g.
phenanthrene), whilst benzo[a]pyrene and other heavy PAHs were an order of magnitude
higher in winter than in summer. Gardner et al. (7) examined atmospheric PAH
concentrations at a semi-urban (Castleshaw) and a rural (Esthwaite Water) site in
northwest England. Lighter, vapour-phase compounds were again quite uniform, but
particulate-bound species increased substantially in the colder months, when residential
wood and coal-fired heating was most prevalent. Similar observations have been made at
monitoring stations in Arctic Canada (8), where the mean ΣPAH concentration during the
colder period (October-April) was an order of magnitude higher than that of the warmer
season.
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Environmental variables exert an influence on ambient PAH concentrations, but this can vary
from place to place and between compounds. Lee and Jones (9) found significant positive
correlations between phenanthrene, fluoranthene and pyrene concentrations and air
temperature during an intensive sampling campaign over many months at Hazelrigg, a semi-
rural site in the northwest of England. In contrast, benzo[b]- and benzo[k]fluoranthene
were negatively correlated to air temperature. Phenanthrene and anthracene also exhibited
a negative correlation with average daily wind speed, whilst wind direction and speed,
humidity, precipitation and pressure were not correlated with any of the heavier PAHs. It
has been suggested that volatilisation of the lighter compounds from soils/vegetation may
contribute to the summer increase of concentrations (9, 10). Studies in urban Birmingham,
UK, found most PAHs were significantly inversely correlated with temperature (11).
However, when the data were corrected to account for the seasonal variation in boundary
layer height, this correlation disappeared for many of the PAHs. Positive relationships with
temperature were then extracted for phenanthrene, fluorene and fluoranthene.
The picture that emerges about seasonality is therefore quite complex, with sources and
environmental variables potentially exerting different influences on different compounds in
different locations. Seasonality and ambient air trends were therefore investigated in more
detail, using various datasets.
Selected datasets, locations and compounds
Sites in the UK, Sweden, Finland and Arctic Canada were selected for study. Their locations
are shown in Figure 2 with some details provided below and in Table 1. Analytical details are
available in the references cited in Table 1. When available, data were compiled for a range
of compounds, namely: acenaphthene (Acen), fluorene (Fluo), phenanthrene (Phen),
anthracene (Anthr), pyrene (Py), fluoranthene (Fla), benzo[b]fluoranthene (B[b]F),
benzo[a]pyrene (B[a]P) and benzo[ghi]perylene (B[ghi]P). For consistency, through this study
winter has been represented by the January-March quarter and summer by July-
September. Data have been compiled accordingly.
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UK sites: The UK Toxic Organic Micro-Pollutants Survey (TOMPs) has operated a network
of sites since 1991, with samples collected at urban and rural locations every 2 weeks. In
recent years, these samples have been bulked to give quarterly samples (January-March;
April-June; July-September; October-December). The longest PAH time series available is
for 2 city centres (London and Manchester) and the semi-rural Hazelrigg site (ca. 5 km
from the Irish Sea and the small city of Lancaster). Hazelrigg may be influenced by the
proximity of the major M6 motorway. Manchester and London concentrations were studied
for the years of 1991-1998, whilst Hazelrigg provided measured data for 1993-2000. The
time series for B[a]P was not continuous at Hazelrigg and therefore omitted from the
study.
The prevailing wind directions tend to transport pollutants from the UK towards continental
Europe and Scandinavia. Data recorded at Scandinavian sites may therefore represent
possible recipients of LRAT from the UK and Continental Europe (16).
Scandinavian sites: PAHs have been monitored at rural locations in Rörvik, Sweden and
Pallas, Finland. Data are available for the years 1994-1999 at Rörvik and 1996-1999 at
Pallas; Acen and Fluo were not monitored at these locations. Extreme winter temperatures
are common in Pallas with rather temperate summers (see Table 1).
Arctic Canada: A monitoring site has been established at a remote site near Alert, Arctic
Canada, with published data only for the first three years of the sampling campaign there
beginning at 1992 (15, 17). The data are reported weekly, but quarterly arithmetic averages
were calculated for this study. The data extend from 1992 to the end of 1996.
Statistical analysis of the data was performed, to test for significant differences in
quarterly (seasonal) air concentrations within any given year (notably differences between
winter and summer), and year-to-year. Winter-to-summer concentration ratios were
calculated for the different sites, compounds and years.
Table 2 gives the typical ranges for most of the target compounds at each site for 1996 as
a reference year. It is clear from Table 2 that the sites differ substantially in PAH
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concentrations and represent a range along an urban, rural and remote gradient. As
expected, Table 2 shows dilution of ambient air concentrations at sites further away from
major source regions. The PAH contamination at the Scandinavian sites is 1-2 orders of
magnitude lower than the urban UK ones, whilst Alert concentrations are almost 1000 times
lower. Elevated concentrations of some light PAHs (most notably Phen) appear at semi-rural
Hazelrigg. The sources are under investigation, but may be due to the proximity to a major
highway (motorway). Table 2 suggests that proximity to source regions drives PAH air
concentrations. This is reinforced by the findings of the statistical analysis discussed
below.
Seasonality
A univariate analysis of variance was performed by the General Linear Model procedure,
using the SPSS Version 10.1 statistical package. The quarterly air concentration was treated
as the dependent variable, with the sequential seasonal data constituting the independent
variable (covariate). The standard deviation of the mean concentration was also determined
for each quarter, together with the Pearson correlation coefficient (r). Higher r2 values
(~0.75) were obtained for the heavier compounds. The standard deviation was, in most
cases, higher that the mean value itself. The data were therefore logarithmically
transformed to reduce skewness, a common practice when examining environmental
datasets. A similar approach was used to examine PAH, PCB and pesticide air data for sites
on Lake Superior, for example (18). The standard deviation/variability in the data was
thereby reduced, making it less likely that outliers drive the observed trends. After
transforming the data, the r2 values increased up to 0.85 for the heavier PAHs, whilst the
values for lighter compounds remained relatively small.
Urban UK Manchester and London: The W:S ratios are summarised in Table 3 for the
individual years and compounds, together with the 8-year average. The following
observations can be made about the data: a) statistically significant seasonal concentration
differences were observed at these sites for the heavier compounds, namely B[b]F, B[a]P
and B[ghi]P. The winter concentrations, in some cases, exceeded the respective summer
ones by more than an order of magnitude, notably in London; b) of the lighter compounds
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(Acen, Fluo, Phen), only Fluo showed a distinct, though weaker, seasonal concentration
pattern in both urban centres, with W:S ratios as high as 5 (Table 3). In contrast, Acen and
Phen showed varying summer and winter trends (i.e. W:S 1); c) similar behaviour is
shown by the intermediate compounds (Fla, Py and Anthr).
To minimize the influence of possible outliers, the 8-year average ratios were also
calculated. These ratios are very similar for most of the compounds in London and
Manchester. One exception to this was B[ghi]P; however, in London this compound gave a
clear outlier in 1996 (see Table 3). If this value is excluded, the ratios are similar to that of
other compounds. The similarities between the long-term seasonal ratios at these two urban
sites are attributed to the influence of ongoing primary emission sources. Local site-specific
factors, such as meteorology, may affect the year-to-year compound differences/ratios,
which are smoothed out on the 8-year averages. Manchester, a smaller city than London,
receives air masses originating both from the more polluted south and the relatively clean
west and north. The higher year-to-year variability shown for most compounds at
Manchester, compared to London, may be influenced by these factors.
W:S values >1 can result from either increased winter concentrations or decreased summer
ones. The former would indicate a major influence of winter emission sources, such as
domestic heating. The latter could be the result of increased depletion mechanisms. To help
discriminate between these two possibilities, the contribution of the W and S quarters to
the annual average concentration was assessed for each of the years 1991-1998 and is
presented in Figure 3. This analysis showed that winter increases accounted directly for the
changes in the W:S for the heavier compounds in both sites and most of the lighter ones in
London. In summary, the similarity in seasonality implies similar controls on ambient levels at
these urban locations. Given that urban centres have ongoing sources of PAHs (see Table 2),
it seems likely that primary emissions exert the dominant influence over these trends.
Semi-rural UK - Hazelrigg: The statistical analysis performed for the Hazelrigg data also
showed significant differences in concentrations between S and W for all heavy compounds,
Py and Phen. There was also a significant difference between autumn and winter
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30
concentrations for those compounds. Acen, B[b]F and B[ghi]P showed W>S, whilst Phen, Fla
and Pyr showed S>W (see Table 3). Hazelrigg was the only site where elevated summer
concentrations, as opposed to lower winter values, resulted in this observation for lighter
compounds. Possible causes include enhanced volatilisation from vegetation/soils or greater
traffic volume during summer on the nearby (~0.5 km) major motorway (people taking annual
holidays, greater day length).
Rural Scandinavia - Rörvik and Pallas: At the coastal Rörvik site, all the compounds (Phen,
Fla, Pyr, B[a]A, B[b]F, B[k]F and Anth) showed significantly different seasonal
concentrations (p-values 1, driven by
elevated winter concentrations. This is suggestive of the importance of elevated winter
emissions, either locally or following LRAT, controlling ambient levels at these rural sites.
Both locations may be influenced by emissions from continental/central Europe, or by local
rural emissions, notably domestic burning of wood.
Interestingly, from Table 3 the W:S ratios of the heavier PAHs tend to increase moving
away from the urban centres. For B[b]F, B[a]P and B[ghi]P the ratios are highest in order of
R/P> H>L/M. Emissions from local domestic sources, where wood/coal are burnt during
winter months for space heating (3) seems the most probable explanation, although
scavenging by vegetation may contribute by reducing the summertime burden of these
compounds at the rural sites.
Alert: It is important to note that winter temperatures at this site can reach 35oC, with
summer temperatures only just exceeding zero (see Table 1). There are also important
seasonal differences in the predominant air mass origins. Briefly, the Arctic lower
atmospheric circulation during winter is characterized by the presence of two oceanic low
(Icelandic and Aleutian) and two continental high (Asiatic and North American) pressure
systems (19). This prevailing meteorology results in air mass movement from the polluted
Eurasian land mass to impact the high Arctic (and, thus, Alert). This explains the high
winter levels of particulate-bound pollutants measured at Alert (20). During summer, the
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31
dominant Asiatic high pressure system breaks down, greatly reducing air flow into the
Arctic from southerly latitudes, resulting in clean air with very low pollutant levels. Indeed,
PAH concentrations measured in the summer samples are often below detection limits (17,
21). Differences between winter and summer concentrations were sometimes 2-3 orders of
magnitude for the multi-ringed compounds (see Table 2). A further analysis of the
seasonality at this remote site was hindered by the extremely low summer values and for
this reason Alert W: S ratios were omitted from Table 3.
Underlying trends
The underlying atmospheric trends of selected PAHs are shown in Figure 4. The X-axis
represents the sequential quarters (seasons) for which data where available, whereas the
natural logarithms of air concentrations are plotted in the Y-axis. Phen and BaP were used
to represent low and high molecular weight compounds, but all other compounds revealed
similar trends. The natural logarithm of air concentrations was selected in order to reduce
the skewness/ scatter of the data. The following observations can be made:
1. London and Manchester show decreases in both the amplitude of the annual
oscillation and the mean yearly value for most of the compounds studied.
Concentrations exhibited a clear decreasing trend at both sites, excluding a peak in
the autumn of 1994 for London. All heavy PAHs show statistically significant long-
term trends, i.e. their rate of year-to-year seasonal concentration decrease follows
the same pattern. Fluo also followed the pattern of its heavier counterparts.
Examination of the data at a finer resolution showed spikiness, presumably the
result of local emission events. Every early November in the UK, for example,
fireworks are set off and bonfires lit across the whole country. Lee et al. (22) have
found significantly elevated levels of combustion-derived polychlorinated-dibenzo-p-
dioxin and dibenzofuran (PCDD/Fs) as a result of such events and similar
observations have been made for PAHs (23).
2. At Hazelrigg, Fla and Py concentrations appear to have increased since 1998. There
are no significant or consistent trends (up or down) for the other compounds, with
large year-to-year variability.
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3. No underlying trends were apparent at Rörvik and Pallas, although the available
datasets are shorter here. Bignert et al. (24) highlighted the importance of long-
term, continuous environmental datasets and the difficulties of interpreting
shorter-term datasets. This emphasises the need for consistent multi-year
monitoring programmes.
4. A decrease of concentrations is evident in Alert over the 1992-1996 period for
most of the studied compounds and is the subject of an ongoing study (25). Over
time concentrations at Alert were represented only by the months of November to
March for the existing five years of data. Most of the summer data fell below the
method detection limit and were, thus, omitted from further analysis.
Derivation of half-lives for declines in atmospheric concentrations
To gain further insight regarding the long-term concentration trends, the natural logarithm
of the quarterly air concentration was regressed with season. Linear trendlines were then
calculated for all 6 sites under study for the years 1991-1999 (or however long samples
were available). If Y is the air concentration and X the time in quarters, half-lives for
declines in atmospheric concentrations can then be calculated from the slope of the line, A
(if a significant decrease is observed) according to the following first-order rate equation:
Ln Y = A X + B (eqn 1)
t1/2 = -Ln 2/ A (eqn 2)
The calculated half-lives (in years) are summarized in Table 4, together with the regression
statistics (r square and p values). Half-lives have only been calculated for the datasets that
are the least uncertain. In other words, when the p-values were low, the confidence of the
calculated half-lives being statistically significant was high and, thus, the selected datasets
represent the long-term concentration trends more reliably. In the case of increased p-
values, the scatter/uncertainty in the data is so high that a half-life term is not meaningful.
This was the case for most compounds at Rörvik and Pallas as well as most light PAHs in
Alert.
Most of the data are noisy, influenced by the short time-series available, and reveal site-
by-site and compound differences. Some trends are apparent, however: generally, the
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33
trends for PAH air concentrations are downwards, though exceptions are apparent (see
Table 4). It has taken approximately 4-8 years for London air concentrations to drop by
50% during the 1990s, whilst there is a greater inconsistency (and longer half-lives) in the
other major urban centre of Manchester. Fla, Py and B[a]A at Hazelrigg showed increasing
trends over the time periods available and are symbolised with (+) in Table 4. In contrast,
rates of decline at Alert through the years 1992-1996 were extremely rapid, especially for
the heavier congeners. Air concentrations at this site are believed to be mainly driven by
primary emissions and LRAT. Local meteorology is likely to exhibit a profound effect for
this remote site, as discussed above. It will be interesting to see how the trends develop
over a longer time period at this location.
Implications of the study
Signatories to the UNECE POPs protocol undertake to reduce national PAH emissions to
1990 levels. However, as discussed and despite efforts at source identification (2, 26),
many countries will experience difficulties in demonstrating compliance, because source
inventories for 1990 and contemporary situations are subject to major uncertainties.
Ambient monitoring data can provide a powerful tool to demonstrate underlying trends
directly and by implication - source reduction. However, this requires reliable and long-
term (many years) datasets because as this study has demonstrated site-by-site
differences in levels and trends can be substantial and subject to considerable short-term
(seasonal; year-on-year) variability.
This study indicates that primary sources continue to drive atmospheric PAH concentrations
in the urban centres. LRAT carries these primary emissions to rural/remote locations,
where they can exert an important influence, with some evidence for this affecting the
sites of Hazelrigg and Rörvik. PAH concentrations in such areas can also be strongly
influenced by local diffusive combustion-derived emissions. The remote site at Alert
revealed strong seasonality, but illustrates the importance of considering the seasonal
dependency of local meteorology.
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A convenient categorisation of PAH sources considers domestic, industrial, mobile (vehicle),
agricultural and natural atmospheric emissions. A recent European Commission (EC) report
concluded that major source components are changing with time as a result of regulation
and economic development (26). Industrial sources are increasingly regulated in Europe,
whilst mobile sources have been subject to more stringent regulation, but not specifically
for PAHs. These factors may collectively contribute to the declining urban PAH
concentrations reported here, although it is perhaps more appropriate to see this as part of
the steady drop in atmospheric PAH concentrations from the 1950/60s observed from long-
term trend records in sediment cores and archived samples (27-29). Agricultural (stubble)
burning has also been controlled in the UK and many other European countries for some
years now.
If further declines in ambient PAH concentrations are desirable, they will be increasingly
difficult to achieve. This study indicates that seasonally-dependent diffusive domestic
combustion sources provide a major component of the primary emissions of PAHs
nationally/regionally. This heightens concern that the targets set by the UNECE protocol
may be difficult to demonstrably meet, because such sources are by their very nature
difficult to quantify, control and reduce. For example, the EC concluded that it is likely
that the continued burning of solid fuels for domestic heating as a source is unlikely to
decrease unless new measures are introduced (26). Our study therefore lends support to
the conclusion that from a cost-benefit perspective, actions to reduce PAH emissions
should focus on domestic burning of wood and coal (30). Such measures include optimisation
of stoves, replacement of open fireplaces with optimised stoves, information campaigns to
promote best practice for combustion, and switching to alternative fuels (30).
Studying the seasonality and long-term trends of air concentrations for semi-volatile
organic compounds such as PAHs is subject to a number of uncertainties and rather poorly
understood environmental processes. The influence of volatilisation from soil, water,
vegetation and urban surfaces is still not well understood. Multi-media modelling may be
useful in helping to assess the influence/relative importance of seasonally dependent
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35
depletion/loss mechanisms, the controlling influence(s) of these mechanisms and of
different emission scenarios.
Acknowledgements
This study was supported by Defra (Department for Environment, Food and Rural Affairs)
funding No. EPG 1/3/169. We thank Dr Knut Breivik (NILU) for critical comments and
advice, and Drs Pierrette Blanchard and Hayley Hung of MSC Downsview, Canada, for access
to the Northern Contaminants database for PAH data from Alert.
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(28) Sanders, G.; Jones, K. C.; Hamilton-Taylor, J.; Dörr, H. Environ. Toxicol. Chem. 1993, 12,
1567-1581.
(29) Wild, S. R.; Jones, K. C.; Johnston, A. E. Atmos. Environ. 1992, 26A, 1299-1307.
(30) European Commission DG Environment, 2001. Economic Evaluation of Air Quality
Targets for PAHs. http://europa.eu.int/comm/environment/index
http://europa.eu.int/comm/environment/index
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37
List of figures
Figure 1: Schematic representation of PAH fate processes.
Figure 2: Monitoring sites under study.
Figure 3: The contribution of the winter and summer quarters to the annual average
concentrations for selected compounds at urban centres.
Figure 4: Phenanthrene and BaP concentration trends. The dashed line shows the limited
data for Alert (see text).
List of tables
Table 1: Site-specific characteristics
Table 2: Ranges of the PAH air concentrations (gas and particle) at the selected sites (in
ng/m3)
Table 3: Calculated winter-to-summer concentration ratios
Table 4: Derived half-lives for declines in atmospheric concentrations (years)
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38
Figure 1
Figure 2
AIR
Soil or water body
Primary emission
Long range transport
OH radical reaction
Microbially mediated degradation
Physical removal (i.e. burial)Occlusion into organic matter
Volatilisation/diffusive deposition
Particle deposition (wet and dry)and washout
-
39
London Fluorene
0.00
0.10
0.20
0.30
0.40
0.50
0.60
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Con
cent
ratio
n fra
ctio
n
London BghiP
0.000.100.200.300.400.500.600.700.800.90
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Con
cent
ratio
n fra
ctio
n
Manchester Fluorene
0.00
0.10
0.20
0.30
0.40
0.50
0.60
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999
Con
cent
ratio
n fra
ctio
n
Winter SummerManchester BbFl
0.00
0.10
0.20
0.30
0.40
0.50
0.60
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999C
once
ntra
tion
fract
ion
Figure 3
-
40
Phenanthrene time-series
-6
-4
-2
0
2
4
6
0 5 10 15 20 25 30 35 40
Sequential quarters
ln c
once
ntra
tion
London ManchesterHazelrigg RorvikPallas Linear (Alert)
B[a]P time-series
-10
-8
-6
-4
-2
0
2
0 5 10 15 20 25 30 35 40
Sequential quarters
ln c
once
ntra
tion
Figure 4
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41
Table 1
Site Coordinates Location Duration of study Frequency of record Typical annual temperature and T range (oC) Reference
London 51° 30, 0°10W Rooftop 1991-1998 Quarterly 10, (5-25) 12, 13
Manchester 53°30N, 2°13W Rooftop 1991-1998 Quarterly 10, (5-20) 12, 13
Hazelrigg 54°2N, 2°45W Field 1993-2000 Quarterly 10, (5-20) 12, 13
Rörvik 57°14´N, 14º35´E 4m above ground 1994-1999 Monthly 7.5, (-17-22) 14
Pallas 67°58´N, 24º08´E 4m above ground 1996-1999 Monthly -1.6, (-30-24) 14
Alert 82°47´N, 62º30´W 4m above ground 1992-1996 Weekly -18, (-35-5) 15
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DRAFT REPORT
DEFRA Modelling the fate and behaviour of POP compounds 42
Table 2
London Manchester Hazelrigg Rörvik Pallas Alert
Acen 0.7-1.5 1-4 0.5-2 N/a N/a 0.001-0.02
Fluorene 3-9 4-20 5-20 N/a N/a 0.01-0.3
Phenanthrene 20-22 20-50 70-160 0.8-3 0.2-0.7 0.02-0.08
Anthracene 1-2 1-4 5-15 0.01-0.1 0.002-0.01 0.002-0.003
Fluoranthene 4-6 5-10 5-10 0.3-1.7 0.1-0.3 0.005-0.07
Pyrene 2.5-5 3.5-8 5-10 0.1-1 0.05-0.2 0.004-0.05
B[a]A 0.2-0.9 0.2-1.6 0.3-0.7 0.01-0.2 0.005-0.02 N/d-0.020
Chrysene 0.5-2 0.4-6 0.25-1 0.05-0.5 0.03-0.04 N/d -0.050
B[b]F 0.2-1.5 0.2-1.5 0.05-1 0.04-0.8 0.02-0.05 N/d -0.012
B[k]F 0.1-1 0.1-1 0.02-0.4 0.01-0.3 0.01-0.02 N/d -0.01
B[a]P 0.05-0.6 0.1-1 N/a 0.01-0.2 0.01-0.03 N/d -0.004
B[ghi]P 0.3-10 0.2-0.8 0.02-0.5 0.02-0.15 0.01-0.04 N/d -0.013
N/a: Not analysed
N/d: Not detected
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DRAFT REPORT
DEFRA Modelling the fate and behaviour of POP compounds 43
Table 3
YEAR 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 Average
M 0.5 0.7 1.2 1.0 1.0 2.6 3.2 3.2 1.7 L 1.7 1.4 1.4 0.7 0.6 1.8 1.8 1.4 1.4 Acen H 0.4 3.3 1.0 4.4 4.1 0.9 2.3 M 1.0 0.8 1.3 3.0 3.0 4.6 3.1 4.2 2.6 L 2.0 3.1 4.0 5.0 3.0 3.0 3.0 2.5 3.2 Fluo H 0.6 2.3 0.9 3.7 3.0 1.7 0.6 1.3 1.8 M 1.0 0.9 0.6 1.6 0.4 1.5 1.3 2.4 1.2 L 0.9 1.2 1.1 0.4 0.4 1.0 1.0 1.2 0.9 H 0.4 0.8 0.2 0.6 0.7 0.7 0.2 0.5 R 5.6 2.5 2.6 5.5 2.6 0.8 3.3
Phen
P 2.3 2.7 4.7 1.8 2.9 M 1.4 1.3 0.7 7.0 1.0 1.3 1.1 1.7 2.0 L 1.7 1.5 2.0 1.0 0.7 1.2 0.9 0.9 1.2 H 0.7 2.1 0.1 0.9 0.6 0.8 0.2 0.3 0.7 R 10.7 4.1 4.3 8.2 3.9 2.7 5.7
Fla
P 1.8 4.7 6.9 3.5 4.2 M 1.5 1.3 0.8 3.3 1.0 1.4 1.2 1.8 1.5 L 1.6 1.8 2.3 1.0 0.8 1.4 1.1 1.0 1.4 H 0.5 0.7 0.1 0.7 0.6 0.6 0.2 0.3 0.4 R 8.4 3.4 4.8 9.0 4.3 2.9 5.5
Py
P 2.3 4.2 7.2 2.3 4.0 M 1.6 1.4 0.8 8.3 3.0 2.1 1.9 1.8 2.6 L 1.8 2.0 2.0 1.0 0.7 1.5 1.5 1.5 1.5 H 0.6 0.3 0.2 0.8 0.6 0.5 0.2 0.2 0.4 R 9.8 5.2 4.7 8.3 2.6 1.6 5.4
Anthr
P 1.9 2.6 28.6 1.1 8.6 M 2.9 5.3 2.2 4.0 2.3 5.2 4.1 3.2 3.6 L 3.7 2.4 3.7 2.3 1.7 6.8 6.7 1.9 3.6 H 10.0 7.0 16.8 10.0 7.4 2.6 1.9 8.0 R 25.1 5.5 13.3 19.1 12.0 3.7 13.1
B[b]f
P 1.9 2.8 6.6 9.0 5.1 M 5.6 7.3 3.7 3.0 7.1 5.8 4.9 5.3 L 4.3 3.3 2.3 5.0 1.5 10.7 12.5 1.5 5.1 H n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a R >30 >5 >7 >20 >19 >34
B[a]P
P >2 >10 >12 >7 M 4.0 3.5 1.8 1.0 1.0 4.4 4.4 4.6 3.1 L 1.2 4.4 4.2 3.3 1.4 41.4 4.1 3.2 7.9 B[ghi]P H 5.0 1.0 1.0 26.5 12.0 >10 9.1
M: Manchester, L: London, H: Hazelrigg, R: Rörvik, P: Pallas Numbers in bold are assumed outliers Values >1 signify winter > summer
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DRAFT REPORT
DEFRA Modelling the fate and behaviour of POP compounds 44
Table 4
London Manchester Hazelrigg Rörvik Pallas Alert
t1/2 r2 p t1/2 r2 p t1/2 r2 p t1/2 r2 p t1/2 r2 p t1/2 r2 p
Acen 4.2 0.454
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Section 4 Manuscript title: Modelling the atmospheric fate and seasonality of polycyclic aromatic hydrocarbons in the UK Authors and affiliations: Konstantinos Prevedouros, Kevin C. Jones and Andrew J. Sweetman Environmental Science Department, Institute of Environmental and Natural Sciences, Lancaster University, Lancaster, LA1 4YQ, United Kingdom. Submission journal: Environmental Toxicology and Chemistry. SETAC press. www.setac.org
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Abstract
This paper presents the results from an exercise in atmospheric compound fate
modelling, which had three main objectives: 1). to investigate the balance between
estimated national atmospheric emissions of 6 selected PAHs and observed ambient
measurements for the UK, as a means of testing the current emission estimates; 2). to
investigate the potential influence of seasonally dependent environmental fate processes
on the observed seasonality of air concentrations; and 3). after undertaking the first
two objectives, to make inferences about the likely magnitude of seasonal differences in
sources. When addressing objective 1 with annually averaged emissions data, it appeared
that the UK PAH atmospheric emissions inventory was reasonably reliable for fluorene,
fluoranthene, pyrene, benzo[a]pyrene and benzo[ghi]perylene but not so for
phenanthrene. However, more detailed analysis of the seasonality in environmental
processes which may influence ambient levels, showed that the directions and/or
magnitudes of the predicted seasonality did not coincide with field observations. This
indicates either that our understanding of the environmental fate and behaviour of
PAHs is still limited, and/or that there are uncertainties in the emissions inventories. It
is suggested that better quantification of PAH sources is needed. For 3- and 4-ringed
compounds, this should focus on those sources which increase with temperature, such as
volatilisation from soil, water, vegetation and urban surfaces, and possible microbially-
mediated formation mechanisms. The study also suggests that the contributions of
inefficient, diffusive combustion processes (e.g. domestic coal/wood burning) may be
underestimated as a source of the toxicologically significant higher molecular weight
species in the winter. It is concluded that many signatory countries to the UNECE POPs
protocol (which requires them to reduce national PAH emissions to 1990 levels) will
experience difficulties in demonstrating compliance, because source inventories for
1990 and contemporary situations are clearly subject to major uncertainties.
-
Introduction
There is considerable interest in the atmospheric sources, behaviour and potential
carcinogenic/mutagenic effects of polycyclic aromatic hydrocarbons (PAHs) [1-3]. They
are amongst the compounds subject to international atmospheric emissions controls
under the 1998 United Nations Economic Commission for Europe (UNECE) protocol [4].
Signatories to the POPs protocol have undertaken to reduce atmospheric emissions of
PAHs to the levels of the reference year 1990. In addition, some countries have
adopted, or are considering, air quality standards for selected PAHs [2]; the United
Kingdom has a proposed annually averaged standard for benzo[a]pyrene of 0.25 ng/m3,
for example. This value can be exceeded in both urban and rural areas, during the winter
months [5].
Despite these regulatory developments, there are still major uncertainties over our
understanding of the atmospheric sources and behaviour of PAHs. National and regional
source inventories are still at best expert estimates, as there are numerous diffusive
and poorly quantified sources of these compounds [2,3]. Some inventories point towards
domestic burning of coal and wood as the dominant source of PAHs to the atmosphere,
others implicate emissions from vehicles, or metal smelting/process operations, for
example. Without reliable information on sources, it will be difficult for signatory
countries to accurately assess whether they are reducing emissions in line with their
commitments to international agreements.
One useful approach to help distinguish between the dominant source categories is to
examine ambient monitoring data. For example, if ambient air measurements display
seasonality, this would provide clues about the dominant sources; some sources are
seasonal (e.g. domestic heating; natural fire events), whilst others are not (e.g. industrial
combustion, aluminium and coke production, petroleum refining). Seasonality of ambient
PAHs is often observed [6]. However, air concentrations are controlled by a complex
array of variables, some of which may also influence the seasonality in ambient air
measurements. Examples include: secondary sources of PAHs into the atmosphere (i.e.
possible volatilisation from soil, water, vegetation or/and urban surfaces); atmospheric
loss/removal processes, such as wet deposition; reactions with OH radicals; scavenging
by vegetation; dilution/advection factors, influenced by wind speed and direction; and
-
mixed boundary layer height. Finally, seasonal temperature changes drive the gas :
particle distribution and atmospheric reaction rates of PAHs.
Modelling is a useful tool in helping to assess the influence/relative importance of
seasonally dependent sources and environmental fate processes on ambient
concentrations. Hence, it can be helpful in identifying which variables are likely to exert
an influence on the seasonality of ambient PAH monitoring data, thereby providing clues
as to the dominant processes and the reliability of emission inventories. This paper
presents the results from a modelling exercise, which had three main objectives:
1. to investigate the balance between estimated national atmospheric emissions of
PAHs and observed ambient measurements for the UK, as a means of testing the
current emission estimates;
2. to investigate the potential influence of seasonally dependent environmental fate
processes on the observed seasonality of air concentrations;
3. after undertaking 1 and 2, to make inferences about the likely magnitude of
seasonal differences in sources.
A dynamic atmospheric fate model was developed and applied to a range of compounds
with contrasting physico-chemical properties and fate characteristics. Six PAHs were
selected for study, namely: fluorene (Fluo), phenanthrene (Phen), fluoranthene (Fla),
pyrene (Py), benzo[a]pyrene (B[a]P) and benzo[ghi]perylene (B[ghi]P). The years 1993-
1997 were chosen as the study period, as source inventory and ambient data is available
for that time, with 1996 selected as a model year. Based on the results of these
objectives, the likely dominant sources of PAHs to the UK atmosphere are discussed,
along with the environmental processes controlling them.
PAH emissions for the UK
PAHs are generally produced as a result of incomplete combustion processes, in oxygen
deficient conditions. A convenient categorisation of PAH sources considers domestic,
industrial, mobile (vehicle), agricultural and natural atmospheric emissions. Most source
inventories focus on these primary or fresh releases of PAHs, although secondary
sources - re-cycling of previously emitted reservoirs in soils, vegetation and sediments -
may also be important, particularly for lower molecular weight species [7,8]. Accidental
-
fires are another source, which are very difficult to quantify and often not included in
inventories.
A recent report concluded that major source components are changing with time as a
result of regulation and economic development [3], which adds to the problems of
attaining a reliable source inventory. Industrial sources are increasingly regulated in
Europe, whilst mobile sources have been subject to more stringent regulation, but not
specifically for PAHs. Agricultural (stubble) burning has also been con